Identification Of Mycotoxin Absorption Materials In Clay Deposits

ABSTRACT

A method for determining absorption properties in clay deposits is provided that includes obtaining a clay sample, preparing the clay sample, analyzing the clay sample, and applying one or more correlative models to the clay sample. Additionally a system for use in determining absorption properties in clay deposits is provided that includes a plurality of inorganic particles, an analytical instrument configured to gather physical and/or chemical data about the inorganic particles, and a computer system configured to accept the physical and/or chemical data and/or generate correlations between the inorganic particles based on the data.

BACKGROUND

Contamination of animal feed represents an ongoing problem foragricultural, animal raising, and food processing industries. Asubstantial portion of animal feed supplies, such as grain and hay,become contaminated by mycotoxins produced by invading molds. Mycotoxinsare carcinogenic metabolites produced by certain types of fungi andmycotoxin formation may occur when the harmful fungi grow on crops inthe field, at harvest, in storage, or during feed processing. One suchmycotoxin is aflatoxin, which may be linked to decreased nutritive valueand instances of poisoning when present in stored grain or other feeds.

Some varieties of clay minerals may be added to animal feed to reducethe bioavailability of aflatoxins. The bioavailability may be reduced bythe binding capabilities of some natural and modified clay minerals tobind to aflatoxin when added to animal feeds to negate or ameliorate thepresence of aflatoxins. One clay type that may be useful as an aflatoxinbinder are bentonites, which are smectite-rich clays and may be foundthroughout the world.

Current approaches for testing clay deposits for aflatoxinabsorption/binding are time intensive and often costly. One reason forthis is that absorption most testing involves collecting clay samplesfrom multiple sources and sending the samples offsite to a wet lab foranalysis.

BRIEF DESCRIPTION OF THE DRAWINGS

These drawings illustrate certain aspects of some of the embodiments ofthe present disclosure and should not be used to limit or define thedisclosure.

FIG. 1 is a schematic view of a block diagram illustrating a processutilized for identification of an absorbency property in clay depositsaccording to an embodiment of the present disclosure;

FIG. 2 illustrates a plot of the predictive performance of the freeswell index for Qmax versus the actual Qmax values for all bentonitesamples according to an embodiment of the present disclosure;

FIG. 3 illustrates a plot of the predictive performance of the freeswell index for Qmax versus the actual Qmax values for blue bentonitesamples according to an embodiment of the present disclosure;

FIG. 4 illustrates a plot of the predictive performance of model #1 forblue bentonite samples according to an embodiment of the presentdisclosure;

FIG. 5 illustrates a plot of the predictive performance of model #2 withblue bentonite samples according to an embodiment of the presentdisclosure;

FIG. 6 illustrates a plot of the predictive performance of model #1 withall bentonite samples according to an embodiment of the presentdisclosure; and

FIG. 7 illustrates a plot of the predictive performance of model #3 withall bentonite samples according to an embodiment of the presentdisclosure.

DETAILED DESCRIPTION

The present disclosure is directed to mycotoxin binders and, inparticular, embodiments, may be directed to methods and systems fordetection of mycotoxin binders in clay deposit materials from a mine. Byway of example, mycotoxin binders, including aflatoxin binders, may bepresent in clay deposits which is then incorporated and processed as anadditive to food stock.

The present disclosure is additionally directed to methods fordetermining the aflatoxin absorption efficacy of clay deposits,including bentonite, at or near a deposit source. Other aspects of thepresent disclosure additionally may be used to identify types ofbentonite that absorb and bind aflatoxin for use in products. Aspects ofthe present disclosure may employ multi-variate modelling to correlateone or more physical and chemical properties of bentonite and itscapacity for binding aflatoxin for the purpose of identifying materialin new and existing clay reserves. Additional aspects of the presentdisclosure may be used to make a determination as to the aflatoxinbinding ability of a clay sample and to categorize the clay sample forplacement in an alpha pile or a beta pile, where the alpha pilecategorization is indicative of a the bentonite sample possessing anaflatoxin binding affinity above a predetermined threshold.

Bentonite is an absorbent aluminum phyllosilicate clay with acomposition that includes various amounts of montmorillonite. Varietiesof bentonite may be region specific and directly reflect the geologicorigin of the source location. Different types of bentonite may be namedafter the respective dominant element, such as potassium (K), sodium(Na), calcium (Ca), and aluminum (Al). Bentonite is usually formed fromthe weathering of volcanic ash, often in the presence of water. Forindustrial purposes, some classes of bentonite include sodium andcalcium bentonite. Exemplary bentonite source locations include Montana,other regions of the United States, France, Spain, Greece, Morocco,Italy, Argentina, China, and Turkey.

In some instances, bentonite may be sourced from a mine or pit site.Depending on the location of the mine, including depth of the bentonitedeposit, the color of the bentonite clay may be present in a differentrange of colors. For example, in the Bighorn basin area of Wyoming, thebentonite clay may be in the blue or yellow range. In the Bighorn basinarea, yellow bentonite clay deposits tend to lie closer to the surfaceof the mine, and may have industrial applicability including use indrilling fluids. Additionally, yellow bentonite may include some ironcontent. Blue bentonite clay deposits may be located less close to thesurface of the mine and have lower performance for use in drillingfluids.

The animal feed market is a large volume industry. As such, customers ofanimal feed mycotoxin binder (bentonite clay) may have high performanceexpectations for binder additives. Accordingly, accurate identificationand characterization of reserves of suitable clay binder additives maybe of competitive importance for bentonite clay market suppliers.Current approaches to identifying suitable bentonite clay binderadditives may require testing of materials from multiple mining pits forbinding performance. Such offsite testing may typically be performedoffsite at a third-party laboratory. Such testing may be both timeconsuming and expensive. Current approaches to performing onsite bindingtesting have presented a number of challenges. One such challenge is dueto the equipment required for aflatoxin binding testing. Anotherchallenge is associated with the health, safety, and environmentalchallenges associated with working with carcinogenic mycotoxin analytes.

In some embodiments, in accordance with the present disclosure, one ormore bulk properties of clay reserves may be analyzed at or near anongoing mining operation to accurately correlate aflatoxin bindingperformance. Other aspects of the present disclosure may alleviate oneor more drawbacks presented by current testing approaches. It should benoted that while multiple published studies have proposed improvementsattempts in testing mycotoxin binding samples, ultimately empiricaltesting of such studies have been inconclusive and/or have shownrelatively low correlation to aflatoxin binding performance. Othercurrent testing approaches, including the ASTM D5890 swell index test,while generally having been acknowledged as a predictor, objective datahave shown that swell index tests may show low correlation to mycotoxinbinder performance.

Present methods for determining clay aflatoxin absorption have largelyrelied upon on a free swell index value to identify certain types ofdesirable materials. One drawback of this approach may be attributed tothe fact that the correlation of clay aflatoxin binding performance andfree swell value of a given clay sample may not be as reliable as therelationship described by multivariate models disclosed herein. A swellindex may also be referred to as free swell index. In soil applications,the free swell index describes when the volume of the soil increaseswithout any application of external forces or water pressure. The indexmeasure indicates the increase in volume with respect to the originalvolume. For clay applications, free swell index tests are commonly usedfor identifying expansive clays and to predict the swelling potential.

Development and use of one or more clay analysis models set forth hereinmay be used to identify certain mycotoxin binding clay reserves for usein feed products in addition to reducing challenges including timeintensive testing durations. Additionally, novel models disclosed hereinmay provide a mycotoxin binding determination using one or moreresulting measurements from X-Ray Diffraction (XRD), X-Ray Fluorescence(XRF), and wet lab evaluations rather than absorption isotherms foraflatoxin. Employing one or more of the models in accordance with thepresent disclosure may decrease the time and expense of qualifying clayreserve materials as an aflatoxin binder, particularly via use ofhandheld or portable testing equipment whereby XRF or XRD readings maybe performed in the field or onsite.

FIG. 1 illustrates a block diagram that may be used to determine one ormore attributes indicative of mycotoxin absorption for one or more claysamples according to an aspect of the present disclosure. In block 10,the step of select pit sites for clay analysis is performed. In block12, the step of obtain clay samples from pit sites is performed. One ormore clay samples may be obtained in a variety of ways, including from aclay deposit source, such as a mine. In block 14, the step of preparecomposite clay samples is performed. Preparation of composite claysamples may include extraction and preparation of clay samples andfurther include crushing, drying, and grinding the clay samples. Block14 may further involve preparation so that the clay sample has arelatively low moisture content (7-8%) and is of a 200-mesh consistency.It will be appreciated that other granularity and mesh values may beused. In block 16, the step of analyze clay samples to predict bindingperformance is performed. Analysis of the clay samples is performed todetermine one or more properties of the clay samples. Clay sampleproperties may include XRD, XRF, free swell index, PH readings, anddetermination of clay composition including minerals, metals, and otherattributes.

In block 18, the step of applying correlation to clay sample analysis isperformed. Block 18 may involve correlating one or more properties ofthe bentonite/clay samples to known bentonite clays to determine thesample capacity for aflatoxin binding. In general, multivariant modelingtechniques as described herein are used to correlate properties with thesample's capacity for aflatoxin binding. Capacity for aflatoxin bindingin clay samples may be represented by Qmax. It will be appreciated thatQmax is shown here in units of mol/kg. In some embodiments, multivariantmodeling may be used to correlate the one or properties of the bentonitesample to the bentonite sample's Qmax.

In block 20, the step of identify pit site reserves based on claycorrelation analysis is performed. Clay sample correlation analysis mayinclude identification of clay deposit locations for later extraction.In block 22, the step of make mining plans based on identified clay pitsite reserves is performed.

As described herein, Qmax refers to the absorbency of a particular claysample. More particularly, the present disclosure sets forth a series ofmultivariate models in which a predicted Qmax is plotted against actualQmax values.

FIG. 2 illustrates a plot of the predictive performance of the freeswell index for Qmax versus the actual Qmax values for all of thebentonite samples according to an embodiment of the present disclosure.As shown, the correlation between free swell and Qmax has an R∧2 of0.2634 and a Root Mean Square Error (RMSE) of 0.0639 versus models whichhave R∧2 values greater than 0.6 and RMSE values under 0.04. Using freeswell alone to predict material with Qmax values greater than or equalto 0.35 would cut off material with a swell index value greater than16-17, which may eliminate material that performs well and includeseveral samples that do not, as shown in the predictive performancetables set forth herein.

FIG. 3 illustrates a plot of the predictive performance of the freeswell index for Qmax versus the actual Qmax values for the bluebentonite samples according to an embodiment of the present disclosure.As depicted, is a plot whereby the Qmax predicted values are obtainedusing only the free swell index versus Qmax actual with RMSE bands forall samples tested and for the ‘blue’ samples. The samples testedoriginally consisted solely of ‘blue’ clay samples, and two multivariatemodels were created using this data. A validation data set was analyzedthat included a wider range of samples including some previouslyuntested ‘yellow’ clay samples. Two multivariate models are used for thefull sample set: model #1 which was identified with the ‘blue’ sampleset and model #3 which applies to both sets.

FIG. 4 illustrates a plot of the predictive performance of model #1 forthe blue bentonite samples according to an embodiment of the presentdisclosure. As shown, aflatoxin binding affinities (Qmax) werecorrelated with results from wet lab, XRD, and XRF testing. Screenedphysical and chemical properties that showed strong correlations wereused in the development of the multivariate models for prediction ofaflatoxin binding performance. One of the strongest correlations of Qmaxwas with the ratio of Magnesium (Mg) to Potassium (K) via XRF analysis.Both models for the ‘blue’ samples use the free swell and Mg/K and haveR∧2 values>0.69. Model #1 uses Mg/K and free swell index. Model #2 usesMg/K, free swell index, cristobalite, and Fe content. A first exemplarymodel is as follows:

Term Estimate Intercept 0.3386 Free Swell Index −0.0064 Wt. % Mg/wt. % Kboth via XRF 0.0400

Qmax=0.3386−(0.0064x swell)+(0.0400x Mg/K)

FIG. 5 illustrates a plot of predicted absorbency blue all clay samplesusing a second model according to an embodiment of the presentdisclosure, whereby Qmax was predicted with the second model versus Qmaxactual with RMSE bands.

Whereby the first model has an R∧2 of 0.69 and an RMSE of 0.0405, asecond exemplary model is as follows:

Term Estimate Intercept −0.0573 Wt. % Mg/wt. % K both via XRF 0.0380Free Swell Index −0.0047 Wt. % Fe by XRF 0.0876 Wt. % Cristobalite byXRD 0.0137

Qmax predicted with Model #2 versus Qmax actual with RMSE bands.

Qmax=−0.0573−(0.0047 x swell)+(0.0380 x Mg/K)+(0.0876 x Fe)+(0.0137 xcristobalite) Model #2 has an R∧2 of 0.82 and an RMSE of 0.0328.

It will be appreciated that both of the aforementioned exemplary modelsmay show improved predictive performance than using the free swell indexalone as a cut off for aflatoxin binder. Turning back to bentonitemodels, the first model uses free swell index determination and theratio of magnesium to potassium may be applied to full sample set withan R∧2 of 0.60 and an RMSE of 0.0482. A third model may use the contentsof calcium, barium, and aluminum as well as the product of the weightfraction of magnesium and the smectite content and has an R∧2 of 0.68and an RMSE of 0.0412.

An exemplary sample set for the first model is as follows:

Term Estimate Intercept 0.3732 Free Swell Index −0.0072 Wt. % Mg/wt. % Kboth via XRF 0.0320

FIG. 6 illustrates a plot of predicted absorbency of all clay samplesusing a first model according to an embodiment of the presentdisclosure. As shown is Qmax predicted with the first model versus Qmaxactual for all samples tested with RMSE bands.

Qmax=0.3732−(0.0072 x swell)+(0.0320 x Mg/K) Model #1 has an R∧2 of 0.60and an RMSE of 0.0482

FIG. 6 illustrates a plot of the predictive performance of model #1 withall of the bentonite samples according to an embodiment of the presentdisclosure. An exemplary third model set is as follows:

Term Estimate Intercept 0.0400 Product of Wt. % smectite 0.0049 by XRDand the wt. fraction of Mg to exchangeable cations all by XRF Wt. % Cavia XRF 0.0467 Wt. % Ba via XRF −0.4059 Wt. % Al via XRF 0.0091

FIG. 7 illustrates a plot of the predictive performance of model #3 withall of the bentonite samples according to an embodiment of the presentdisclosure. As shown, Qmax predicted with third model versus Qmax actualfor all samples tested with RMSE bands. Qmax=0.0400+(0.0049 x Mg tosmectite)+(0.0467 x Ca)− (0.4059 x Ba)+(0.0091 x Al) Model #3 has an R∧2of 0.68 and an RMSE of 0.0412.

The multivariate models discussed herein have stronger correlations thanthe free swell alone. Additionally, validation sets have been performedto quantify model performance. A random subset of samples was removedfrom the main set and the models were re-made without the subsetincluded. Another model was then used to predict the Qmax values of theremoved subset given the analytical data for those samples. The thirdmodel predicted the performance of both blue and yellow samples well.However, first and second models performed well for the ‘blue’ bentonitesamples with low fluid performances, whereas predictions for the‘yellow’ samples and the high fluid performance ‘blue’ samples were offby more than 20%. Embodiments in accordance with the instant disclosure,as compared to prior published studies, may indicate improvedperformance. It will be appreciated that prior approaches, based in parton the selected absorption metric (such as swell index or d-001 spacing)were only able produce moderate correlation, below the performance ofone of more of models in this disclosure.

TABLE Summary of Models Clay No. of Model Type(s) Data PointsR{circumflex over ( )}2 RMSE Only Swell Blue 24 0.54 0.048 Only SwellAll 29 0.26 0.064 #1 Blue 24 0.69 0.041 #1 All 29 0.60 0.048 #2 Blue 240.82 0.033 #3 All 37 0.68 0.041

TABLE Predictive Performance Plots Only Swell with Predicted Blue Clays≥0.35 <0.35 Actual ≥0.35 10 2 <0.35 2 10 Only Swell with Predicted AllClays ≥0.35 <0.35 Actual ≥0.35 10 5 <0.35 2 12 Model #1 with PredictedBlue Clays ≥0.35 <0.35 Actual ≥0.35 11 1 <0.35 0 12 Model #1 withPredicted All Clays ≥0.35 <0.35 Actual ≥0.35 12 3 <0.35 0 14 Model #2with Predicted Blue Clays ≥0.35 <0.35 Actual ≥0.35 10 2 <0.35 0 12 Model#3 with Predicted All Clays ≥0.35 <0.35 Actual ≥0.35 18 2 <0.35 0 17

Additionally, individual correlations of the cations (Na, Ca, K, and Mg)may be used to screen samples for capacity to bind aflatoxin. From theanalytical data gathered, aflatoxin binding may favor higher magnesiumand calcium levels and lower levels of potassium and sodium. The percentby weight of illite in the samples may also be used as a screen, withsamples that are <1% by weight illite favored for aflatoxin binding.Layer spacing may also reflect the trend of increased binding withincreased calcium in the bentonite samples tested; samples that arepredominantly calcium based on their d-001 layer spacing have higherQmax values than mixed sodium calcium and predominantly sodium samples.

The preceding description provides various examples of the systems andmethods of use disclosed herein which may contain different method stepsand alternative combinations of components.

Statement 1. A method for determining absorption properties in claydeposits comprising: obtaining a clay sample, preparing the clay sample,analyzing the clay sample, and applying one or more correlative modelsto the clay sample.

Statement 2. The method of statement 1 wherein the step of preparing theclay sample includes drying the clay sample.

Statement 3. The method of any preceding statement wherein the step ofpreparing the clay sample includes crushing the clay sample.

Statement 4. The method of any preceding statement wherein the step ofanalyzing the clay sample includes performing X-Ray diffraction.

Statement 5. The method of any preceding statement wherein the step ofanalyzing the clay sample includes performing X-Ray fluorescence.

Statement 6. The method of any preceding statement wherein the step ofanalyzing the clay sample includes performing X-Ray fluorescence anddetermining a free swell value.

Statement 7. The method of statement 6 further including performingX-Ray diffraction.

Statement 8. A method of determining absorption properties in claydeposits comprising: obtaining a clay sample, preparing the clay sample,analyzing the clay sample, applying one or more correlative models tothe clay sample, and determining the mycotoxin binding performance ofthe clay sample.

Statement 9. The method of statement 8 further comprising the step ofcategorizing the clay sample into an alpha pile or a beta pile.

Statement 10. The method of statement 8 or statement 9 wherein the stepof preparing the clay sample includes crushing the clay sample.

Statement 11. The method of any one of statements 8 to 10 wherein thestep of analyzing the clay sample includes performing X-Ray fluorescenceand determining a free swell value.

Statement 12. The method of any one of statements 8 to 11 wherein thestep of analyzing the clay sample includes performing X-Rayfluorescence.

Statement 13. The method any one of statements 8 to 12 wherein the stepof analyzing the clay sample includes performing X-Ray diffraction anddetermining a free swell value.

Statement 14. A system for use in determining absorption properties inclay deposits: a plurality of inorganic particles; an analyticalinstrument configured to gather physical and/or chemical data about theinorganic particles; and a computer system configured to accept thephysical and/or chemical data and/or generate correlations between theinorganic particles based on the data.

Statement 15. The system of statement 14 wherein at least one of theinorganic particles comprises bentonite.

Statement 16. The system of any one of statements 14 to 15 wherein theanalytical instrument is configured to perform X-Ray fluorescence.

Statement 17. The system of any one of statements 14 to 16 wherein theanalytical instrument is configured to perform X-Ray fluorescence anddetermine a free swell value.

Statement 18. The system of any one of statements 14 to 17 wherein theanalytical instrument is configured to perform X-Ray diffraction.

Statement 19. The system of any one of statements 14 to 18 wherein theanalytical instrument is configured to perform X-Ray diffraction anddetermine a free swell value.

Statement 20. The system of any one of statements 14 to 19 wherein theanalytical instrument is configured to perform X-Ray fluorescence, X-Raydiffraction, and determine a free swell value.

It should be understood that, although individual examples may bediscussed herein, the present disclosure covers all combinations of thedisclosed examples, including, without limitation, the differentcomponent combinations, method step combinations, and properties of thesystem. It should be understood that the compositions and methods aredescribed in terms of “comprising,” “containing,” or “including” variouscomponents or steps, the compositions and methods may also “consistessentially of” or “consist of” the various components and steps.Moreover, the indefinite articles “a” or “an,” as used in the claims,are defined herein to mean one or more than one of the element that itintroduces. The term “coupled” means directly or indirectly connected.

For the sake of brevity, only certain ranges are explicitly disclosedherein. However, ranges from any lower limit may be combined with anyupper limit to recite a range not explicitly recited, as well as, rangesfrom any lower limit may be combined with any other lower limit torecite a range not explicitly recited, in the same way, ranges from anyupper limit may be combined with any other upper limit to recite a rangenot explicitly recited. Additionally, whenever a numerical range with alower limit and an upper limit is disclosed, any number and any includedrange falling within the range are specifically disclosed. Inparticular, every range of values (of the form, “from about a to aboutb,” or, equivalently, “from approximately a to b,” or, equivalently,“from approximately a-b”) disclosed herein is to be understood to setforth every number and range encompassed within the broader range ofvalues even if not explicitly recited. Thus, every point or individualvalue may serve as its own lower or upper limit combined with any otherpoint or individual value or any other lower or upper limit, to recite arange not explicitly recited.

Therefore, the present examples are well adapted to attain the ends andadvantages mentioned as well as those that are inherent therein. Theparticular examples disclosed above are illustrative only and may bemodified and practiced in different but equivalent manners apparent tothose skilled in the art having the benefit of the teachings herein.Although individual examples are discussed, the disclosure covers allcombinations of all of the examples. Furthermore, no limitations areintended to the details of construction or design herein shown, otherthan as described in the claims below. Also, the terms in the claimshave their plain, ordinary meaning unless otherwise explicitly andclearly defined by the patentee. It is therefore evident that theparticular illustrative examples disclosed above may be altered ormodified and all such variations are considered within the scope andspirit of those examples. If there is any conflict in the usages of aword or term in this specification and one or more patent(s) or otherdocuments that may be incorporated herein by reference, the definitionsthat are consistent with this specification should be adopted.

What is claimed is:
 1. A method for determining absorption properties inclay deposits comprising: obtaining a clay sample; preparing the claysample; analyzing the clay sample; and applying one or more correlativemodels to the clay sample.
 2. The method of claim 1 wherein the step ofpreparing the clay sample includes drying the clay sample.
 3. The methodof claim 1 wherein the step of preparing the clay sample includescrushing the clay sample.
 4. The method of claim 1 wherein the step ofanalyzing the clay sample includes performing X-Ray Diffraction.
 5. Themethod of claim 1 wherein the step of analyzing the clay sample includesperforming X-Ray Fluorescence.
 6. The method of claim 1 wherein the stepof analyzing the clay sample includes performing X-Ray Fluorescence anddetermining a free swell value.
 7. The method of claim 6 furtherincluding performing X-Ray Diffraction.
 8. A method of determiningabsorption properties in clay deposits comprising: obtaining a claysample; preparing the clay sample; analyzing the clay sample; applyingone or more correlative models to the clay sample; and determiningmycotoxin binding performance of the clay sample.
 9. The method of claim8 further comprising the step of categorizing the clay sample into analpha pile or a beta pile.
 10. The method of claim 8 wherein the step ofpreparing the clay sample includes crushing the clay sample.
 11. Themethod of claim 8 wherein the step of analyzing the clay sample includesperforming X-Ray Fluorescence and determining a free swell value. 12.The method of claim 8 wherein the step of analyzing the clay sampleincludes performing X-Ray Fluorescence.
 13. The method of claim 8wherein the step of analyzing the clay sample includes performing X-RayDiffraction and determining a free swell value.
 14. A system for use indetermining absorption properties in clay deposits: a plurality ofinorganic particles; an analytical instrument configured to gatherphysical and/or chemical data about the inorganic particles; and acomputer system configured to accept the physical and/or chemical dataand/or generate correlations between the inorganic particles based onthe data.
 15. The system of claim 14 wherein at least one of theinorganic particles comprises bentonite.
 16. The system of claim 14wherein the analytical instrument is configured to perform X-Rayfluorescence.
 17. The system of claim 14 wherein the analyticalinstrument is configured to perform X-Ray fluorescence and determine afree swell value.
 18. The system of claim 14 wherein the analyticalinstrument is configured to perform X-Ray diffraction.
 19. The system ofclaim 14 wherein the analytical instrument is configured to performX-Ray diffraction and determine a free swell value.
 20. The system ofclaim 14 wherein the analytical instrument is configured to performX-Ray fluorescence, X-Ray diffraction, and determine a free swell value.